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Asian Journal of Plant Science and Research, 2015, 5(3):24-33

ISSN : 2249-7412

CODEN (USA): AJPSKY

24 Pelagia Research Library

Carbon sequestration potential of tropical deciduous forests of Nallamalais, India

Vendrapati Srinivasa Rao and Boyina Ravi Prasad Rao*

Biodiversity Conservation Division, Department of Botany, Sri Krishnadevaraya University, Anantapur, Andhra

Pradesh, India _____________________________________________________________________________________________ ABSTRACT We estimated the standing biomass and carbon sequestration potential of tropical deciduous forests of Nallamalais, a centre of plant diversity located in the state of Andhra Pradesh, India. A total of 30 randomly stratified sample sites comprising 12 ha area were inventoried following a non-destructive method. The total standing biomass and carbon stocks of the study area are estimated as 56.047 Mt and 26.34 Mt respectively. Among all life forms, trees are the main contributors of standing biomass and carbon stocks in the study area accounting for 96.72% of the above-ground live biomass. The carbon stock accounted for Nallamalais is equivalent to 97.568 Mt of sequestered atmospheric carbon dioxide. With respect to total carbon stock of Indian forests worked out in different studies, Nallamalais share 0.26% to 0.90% of the total carbon stocks of India. Key words: Carbon stocks, Eastern Ghats, Nallamalais, standing biomass, tropical deciduous forests. _____________________________________________________________________________________________

INTRODUCTION

Tropical forests harboring rich biodiversity are responding in several ways to global climate change leading to shifts in species composition and overall increase in turnover [1]. Forest vegetation contains over 350,000 Tg (Tera gram=1012 grams) of carbon, of which tropical forests accounts for 40% and play a major role in global carbon cycle [2]. Estimation of above-ground biomass (AGB) is an essential aspect of carbon sequestration studies since it constitutes about 60% of total phytomass [3]. Tree inventories are still an efficient way of assessing forest carbon stocks and emission to the atmosphere during deforestation [4]. The major carbon pools in India are estimated based on very coarse resolution data and extrapolation because the primary data for the many regions of the country are non-existed or over-estimated [5]. Due to the lack of reliable data on standing biomass and rates of forest degradation, the net carbon emission estimates for India are highly variable [6]. Thus, the improved quantification of carbon pools and fluxes in forest ecosystems is important for understanding the contribution of forests to net carbon emissions and their potential for carbon sequestration [7]. The present study is oriented to estimate carbon sequestration potential of Nallamalais, as a part of Vegetation Carbon Pool (VCP) assessment under National Carbon Project under Geosphere Biosphere Programme of Indian Space Research Organization.

MATERIALS AND METHODS

Study Area Nallamalais, one of the 234 Centers of Plant Diversity of the world [8], lies between 15° 20' to 16° 30' Northern Latitude and 78° 30' to 80° 10' Eastern Longitudes and located in the Eastern Ghats of Andhra Pradesh, India (Fig.

Vendrapati Srinivasa Rao and Boyina Ravi Prasad Rao Asian J. Plant Sci. Res., 2015, 5(3):24-33 _____________________________________________________________________________

1). It spreads in five districts such as Guntur, Kurnool, Nalgonda, Mahaboobnagar and Prakasam. The hill ranges extended over an area of 7640 sq. km. The elevation ranges 300-950m above MSL. The average annual temperature varies from 24 to 29°C and average annual rainfall is 740 mm. The geological formation known as the ‘Archaens’, the non-fossiliferous rocks formed about 2000 million years ago. The major rivers are Krishna and Gundlakamma. The soils are red, black and mixed type. The vegetation is tropical deciduous and scrub type [9]. The primitive tribe ‘Chenchus’ live amidst the forests of Nallamalais. There are two Protected Areas in the study area are Nagarjuna Sagar-Srisailam Tiger Reserve (NSTR) which is the largest tiger reserve in India and Gundlabrahmeswaram (GBM) Wildlife Sanctuary. Methodology In the present study, a non-destructive approach of biomass estimation was done in 30 randomly stratified sampled sites comprising 12 ha area. A comprehensive format design of Vegetation Carbon Pool Assessment Project by Indian Institute of Remote Sensing (IIRS) [10] was followed and this has been the source of identifying the sample sites (250×250 m) based on forest type (available at IIRS under different projects), forest density and IRS LISS III data for Normalized Difference Vegetation Index (NDVI) values ranging between 0.0-0.5. On field, the sites were located with the help of Global Positioning System (GPS) and Survey of India reference topographic maps. Sampling Design For trees/liana enumeration, 250×250 m site area was divided into 4 plots (NE, NW, SE and SW) of size 31.62×31.62 m (i.e., 0.1 ha), about 75-90 m away from the centre [11], [12]. Girth at Breast Height (GBH) measurements were taken with measuring tape and height was measured using Opti-logic digital hypsometer. For enumeration of shrubs, two quadrates of 5×5 m were laid in opposite corners in each 0.1 ha plot and in each quadrate, the number of bushes and tillers in each bush were counted. For herbs and litter, 5 quadrates (4 in corners and 1 in centre) of 1×1 m were laid in each 0.1 ha sample plot and the material is harvested for determining fresh and dry weight. Estimation of Biomass Basal area of each tree/liana was calculated by using standard formula and treated as the critical parameter for estimating trees/liana above ground biomass [13]. Basal Area (m2 ha-1) = πr2 × 10 Volume of each tree/liana with ≥10 cm diameter was estimated using species specific volumetric equation and for species without specific volumetric equations, common equation is applied based on Forest Survey of India [14]. Specific gravity values of different species were selected from literature [15], [16], [17]. Specific gravity values are available for 75-80% stems. For species with unknown specific gravity, the arithmetic mean of all known species was substituted and used in particular sample plot following Brown et al., [18]. Volume of trees/liana with ≥10 cm diameter was converted into biomass by multiplying with specific gravity [19]. Biomass of all the trees was summed to obtain biomass for 0.1ha plot. Biomass (tonnes) = Volume (m3) × Specific Gravity Since volumetric equations for trees/liana with <10 cm diameter are not available, we followed the methodology developed for Vegetation Carbon Pool Assessment Project [11], [12] to estimate biomass of this class. The regression equation developed by correlating basal area and biomass of trees ≥10cm diameter is as follows (Fig. 2). Y=3.6808*X+0.264. Where, Y=Biomass, X=Basal area of trees (>10cm diameter and <10cm diameter), 3.6808 & 0.264=Coefficients The biomass of trees with ≥10 cm diameter and <10 cm diameter in each plot were added together to get biomass of 0.1ha plot.

For shrubs, herbaceous and litter, the mean dry weight (g) is directly taken as biomass. Biomass of trees/liana, shrubs and herbaceous were added to get above-ground live biomass (AGLB). A conversion factor of 20% is used to calculate dead wood biomass from AGLB following Achard et al., [20]. Litter and dead wood biomass were summed up to get above-ground dead biomass (AGDB) and Total above-ground biomass (TAGB) is calculated by adding AGLB and AGDB. In the present study, 20% of the TAGB was considered as below ground biomass (BGB) following Ramankutty et al., [21]. Total biomass (TB) for each sample plot was obtained by addition of TAGB with BGB. Estimation of Carbon Stocks Carbon stocks were estimated from the total biomass by multiplying with IPCC default carbon fraction of 0.47 [22] as follows. Carbon (tonnes) = Biomass (tonnes) × Carbon %

We used Mean Biomass Density Method (MBM) [23] for extrapolation in which mean density is multiplied with forest area.

RESULTS AND DISCUSSION Species Diversity A total of 306 plant taxa belonging to 215 genera and 61 families were recorded in the sampled inventory. The dominant family is Fabaceae (54 species) followed by Poaceae (32 species). With respect to life forms, trees are represented by 124 species; liana 6 species; shrubs 18 species and herbs 158 species. Standing Biomass Trees/liana Biomass A total of 14199 trees/liana individuals were enumerated in the sampled plots in a range of 26-357 individuals per plot. The mean basal area of trees/liana is 17.47±10.99 m2 ha-1 and ranges 1.66-85.62 m2 ha-1 (Table 1), these mean values are on par with tropical dry evergreen forests of Peninsular India [24]. The growing stock density of trees/liana having ≥10 cm diameter is 106.15±65.95 m3 ha-1 and ranges 4.70-372.73 m3 ha-1 in the sampled plots. The total growing stock of the study area is accounted for 81.098 Mm3. While in dry deciduous and secondary dry deciduous forests of Kolli hills [25], the estimated mean volume density is 316.060 m3 ha-1 and 216.673 m3 ha-1 respectively, it is 59.79 m3 ha-1 for Indian forests in 2005 [26]. The mean biomass density of trees/liana with ≥10cm diameter is 55.38±41.30 Mg ha-1 and ranges 0.74-205.95 Mg ha-1 in the sampled plots. Correlation of basal area and biomass of trees with ≥10 cm diameter revealed a determination coefficient of R2 as 0.8704 (Fig. 2). High correlation of biomass with basal area was reported by [12], [18], [27], [28] and according to Clark et al., [29] tree above-ground biomass is strongly correlated with trunk diameter. The mean biomass density of trees/liana <10 cm diameter is 8.80±9.6 Mg ha-1 and ranges 1.25-93.35 Mg ha-1 in the sampled plots. For Indian forests, 29.7% biomass was estimated for the same diameter class [27] which is comparatively higher than the present estimates. Trees/Liana is contributing 49.041Mt biomass with a mean density of 64.19±42.63 Mg ha-1, in a range of 5.20-299.30 Mg ha-1 across sampled plots (Table 1). In comparison, tropical dry evergreen forests of peninsular India [17] registered a range of 39.69-170.02 Mg ha-1 mean density with respect to basal area and 73.06-173.10 Mg ha-1 when basal area and height combined. The present study results are fall in the range with respect to former and found lower with respect to latter. Shrub Biomass Shrubs contribute 0.58 Mt biomass, with a mean density of 0.76±0.64 Mg ha-1 in a range of 0.01-2.82 Mg ha-1 (Table 1) across the plots sampled. These estimates are within the range (0.26-1.43 Mg ha-1) reported from disturbed tropical dry deciduous teak forests of India [30]. Shrub biomass density of 0.116-2.496 Mg ha-1 and 1.08±0.8 Mg ha-1 was reported for mixed dry deciduous forests [31] and mixed plantation [32]. Present study results were within this range compared with former and lower than the latter. Herbaceous Biomass

A total of 1.41Mt biomass is contributed by herbs with a mean biomass density of 1.85±1.11 Mg ha-1 and varied between 0.20-6.00 Mg ha-1 (Table 1) in the sampled plots. Herb biomass range of 1.00-1.59 Mg ha-1 was reported from disturbed tropical dry deciduous teak forests of India [30] and in mixed deciduous forests it was 0.038-0.213 Mg ha-1 [31]. Above-Ground Live Biomass (AGLB) AGLB constitutes 50.69 Mt with mean density of 66.36±42.87 Mg ha-1 and ranges 6.22-302.58 Mg ha-1 (Table 1) in the sampled plots. A total biomass of 14.904-63.249 Mg ha-1 was reported in mixed dry deciduous forests of India [31] and present study values are near to the upper end of these estimates. Litter Biomass Litter constitutes 0.33 Mt with a mean density of 0.44±0.36 Mg ha-1 and ranges 0.02-1.34 Mg ha-1 (Table 1) across the sampled plots. However, higher values of litter biomass density (1.52±1.1 Mg ha-1) from the mixed plantation of India [32] and tropical wet evergreen forests (3.5-4.2 Mg ha-1) of Western Ghats [33] are estimated. Dead Wood Biomass Mean density is 3.20±2.13 Mg ha-1 (equaling 1.51 Mg C ha-1) and ranges 0.26-14.97 Mg ha-1 (Table 1) in the plots sampled and accounts for 2.44 Mt for the study area. Dead wood is generally tends to ignore in many forest carbon budgets, because it does not correlate with any index of stand structure [34]. However, it is having its importance in aspects related to biological diversity [35] and to atmospheric carbon cycle [36]. Above-Ground Dead Biomass (AGDB) The mean density is 3.65±2.21 Mg ha-1 and ranges 0.31-15.94 Mg ha-1 (Table 1) in plots and accounts for 2.78 Mt for the study area. It is 3.6 Mg ha-1 in case of South and South-East Asia [37]. The AGDB of world forests [38] was estimated from none to >600 Mg ha-1. When compared, the present study estimates are absolutely as such that of South and South-East Asia forests and at the lower end of the world forests. Total Above-Ground Biomass (TAGB) The TAGB density is 70.02±45.05 Mg ha-1 and ranges 6.53-318.52 Mg ha-1 (Table 1) across the sampled plots and accounts for 53.49 Mt for the study area. Our results are within the range when compared with disturbed tropical dry deciduous teak forests (28.12-85.26 Mg ha-1) of India [30] and Indian forests (14-210 Mg ha-1) [27]. However, Indian tropical deciduous forests registered high TAGB (97.3 Mg ha-1) [27]. Corresponding to Indian forests TAGB (9793.794 Mt) [39], Nallamalais accounts for 0.54% of the total. Deciduous forests of Western Ghats [40] registered a mean AGB of 280±72.5 Mg ha-1 based on ground data and 297.6±55.2 Mg ha-1 based on Remote Sensing, both values are greater than the present study. In dry deciduous and secondary dry deciduous forests of Kolli hills [25], estimated total biomass density is 251.653 Mg ha-1 and 241.773 Mg ha-1 respectively which are higher than the present study. Below Ground Biomass (BGB) BGB accounts for 2.551 Mt with a mean density of 3.34±2.14 Mg ha-1 and ranges 0.31-15.18 Mg ha-1 (Table 1) in the sampled plots. BGB of Indian forests [39] was estimated at 2605.149 Mt, and Nallamalais accounts for 0.09%. BGB density in a range of 9.01-15.62 Mg ha-1 was reported from disturbed tropical dry deciduous teak forests of India [30] which is greater than the present study. Total Biomass (TB) The mean density is 73.36±47.20 Mg ha-1 and varied between 6.84-33.69 Mg ha-1 (Table 1) in the sampled plots and accounts for 56.047 Mt for the study area. Nallamalais contribute 0.62% to total biomass of Indian forests (8955.434 Mt) [39]. Total biomass in a range of 37.12-100.88 Mg ha-1 was reported from disturbed tropical dry deciduous teak forest of India [30] and present study results fall within this range. Biomass represents the largest organic carbon pool in mature tropical forest ecosystem. The change in forest biomass is considered as key characteristic of forest ecosystem [41]. Biomass variability can be explained by several factors like climate, topography, soil fertility, water supply and wood density, distribution of tree species, tree functional type and forest disturbance [42].

TABLE 1: Standing Biomass (Mg ha-1) and Carbon stocks (Mg ha-1) in various components of the sampled inventory

S. No.

Plot ID Trees/Liana Shrub

AGB Herbaceous

AGB AGLB Litter Dead Wood AGDB TAGB BGB TB Carbon

TNI BA AGB 1 1a 167 8.05 24.36 - 0.75 25.11 0.35 1.22 1.57 26.68 1.26 27.94 13.13 2 1b 229 6.16 20.03 - 0.82 20.85 0.31 1 1.31 22.16 1.04 23.2 10.91 3 1c 238 10.88 35.28 - 0.71 35.99 0.49 1.76 2.25 38.24 1.8 40.04 18.82 4 1d 239 9.69 34.57 - 1 35.57 0.52 1.73 2.25 37.82 1.78 39.6 18.61 5 2a 343 14.46 54.79 - 1.6 56.39 0.55 2.74 3.29 59.68 2.82 62.5 29.37 6 2b 214 10.81 31.64 - 0.89 32.53 0.43 1.58 2.01 34.54 1.63 36.17 17 7 2c 188 9.36 32.43 - 1.8 34.23 0.2 1.62 1.82 36.05 1.71 37.76 17.75 8 2d 357 12.63 45.81 - 0.95 46.76 0.29 2.29 2.58 49.34 2.34 51.68 24.29 9 3a 76 7.59 30.92 - 0.42 31.34 0.51 1.55 2.06 33.4 1.57 34.97 16.43 10 3b 170 12.59 46.85 - 0.2 47.05 0.44 2.34 2.78 49.83 2.35 52.18 24.53 11 3c 194 12.44 75.54 - 0.38 75.92 0.27 3.78 4.05 79.97 3.8 83.77 39.37 12 3d 131 11.05 43.44 - 0.4 43.84 0.54 2.17 2.71 46.55 2.19 48.74 22.91 13 4a 152 7.22 26.98 - 2.2 29.18 0.04 1.35 1.39 30.57 1.46 32.03 15.05 S.

No. Plot ID Trees/Liana Shrub

AGB Herbaceous

AGB AGLB Litter Dead Wood AGDB TAGB BGB TB Carbon TNI BA AGB

14 4b 117 14.93 34.51 - 0.6 35.11 0.07 1.73 1.8 36.91 1.76 38.67 18.17 15 4c 60 8.43 19.79 - 5.5 25.29 0.04 0.99 1.03 26.32 1.26 27.58 12.96 16 4d 65 9.44 40.2 - 6 46.2 0.08 2.01 2.09 48.29 2.31 50.6 23.78 17 5a 84 7.95 20.05 - 3.902 23.95 0.46 1 1.46 25.41 1.2 26.61 12.51 18 5b 107 2.91 11.69 - 3.305 14.99 0.27 0.58 0.85 15.84 0.75 16.59 7.8 19 5c 26 7.67 26.38 - 0.5 26.88 0.34 1.32 1.66 28.54 1.34 29.88 14.05 20 5d 73 13.98 76.46 - 1.3 77.76 0.47 3.82 4.29 82.05 3.89 85.94 40.39 21 6a 101 3.04 10.63 - 1.223 11.85 0.26 0.53 0.79 12.64 0.59 13.23 6.22 22 6b 62 1.66 5.2 - 1.025 6.22 0.05 0.26 0.31 6.53 0.31 6.84 3.22 23 6c 102 3.44 8.99 - 2 10.99 0.27 0.45 0.72 11.71 0.55 12.26 5.76 24 6d 90 2.44 7.7 - 0.964 8.66 0.38 0.39 0.77 9.43 0.43 9.86 4.64 25 7a 134 19.83 71.76 - 3.272 75.03 0.45 3.59 4.04 79.07 3.75 82.82 38.93 26 7b 141 21.89 62.57 - 1.628 64.19 0.3 3.13 3.43 67.62 3.21 70.83 33.29 27 7c 155 19.82 57.02 - 1.061 58.08 0.17 2.85 3.02 61.1 2.9 64 30.08 S.

AGB Herbaceous

28 7d 143 18.65 68.93 - 1.285 70.21 0.38 3.45 3.83 74.04 3.51 77.55 36.45 29 8a 44 2.88 11.05 - 0.846 11.89 0.06 0.55 0.61 12.5 0.59 13.09 6.15 30 8b 105 5.3 22.09 - 0.629 22.71 0.17 1.1 1.27 23.98 1.14 25.12 11.8 31 8c 93 3.86 13.02 0.25 0.648 13.91 0.1 0.65 0.75 14.66 0.7 15.36 7.22 32 8d 112 4.59 22.96 - 0.904 23.86 0.07 1.15 1.22 25.08 1.19 26.27 12.35 33 9a 134 10.07 29.27 - 1.21 30.48 0.08 1.46 1.54 32.02 1.52 33.54 15.77 34 9b 131 10.64 30.63 - 1.806 32.43 0.2 1.53 1.73 34.16 1.62 35.78 16.82 35 9c 61 5.5 13.52 - 1.615 15.13 0 0.68 0.68 15.81 0.76 16.57 7.79 36 9d 65 10.35 24.28 - 1.486 25.76 0.04 1.21 1.25 27.01 1.29 28.3 13.3 37 10a 129 16.03 63.2 - 1.224 64.42 0.13 3.16 3.29 67.71 3.22 70.93 33.34 38 10b 140 19.49 78.35 - 1.302 79.65 0.26 3.92 4.18 83.83 3.98 87.81 41.27 39 10c 138 13.97 54.47 - 1.487 55.95 0.09 2.72 2.81 58.76 2.8 61.56 28.93 40 10d 113 6.52 33.25 - 1.245 34.49 0.19 1.66 1.85 36.34 1.72 38.06 17.89 41 11a 156 30.29 133.55 - 1.118 134.66 0.52 6.68 7.2 141.86 6.73 148.59 69.84 S.

AGB Herbaceous

42 11b 147 27.5 110.8 - 1.54 112.34 0.22 5.54 5.76 118.1 5.62 123.72 58.15 43 11c 159 26.42 95.66 - 1.498 97.15 0.28 4.78 5.06 102.21 4.86 107.07 50.32 44 11d 143 23.32 107.6 - 0.994 108.59 0.1 5.38 5.48 114.07 5.43 119.5 56.16 45 12a 89 37.16 104.78 1.88 0.782 107.43 0.98 5.24 6.22 113.65 5.37 119.02 55.94 46 12b 96 31.1 106.53 0.9 1.016 108.43 0.75 5.33 6.08 114.51 5.42 119.93 56.37 47 12c 102 21.73 62.72 0.42 1.066 64.2 0.82 3.14 3.96 68.16 3.21 71.37 33.54 48 12d 98 29.39 71.68 1.43 1.028 74.12 0.67 3.58 4.25 78.37 3.71 82.08 38.58 49 13a 107 30.48 116.97 - 0.41 117.38 0.13 5.85 5.98 123.36 5.87 129.23 60.74 50 13b 106 33.84 138.65 - 0.765 139.41 0.2 6.93 7.13 146.54 6.97 153.51 72.15 51 13c 114 28.66 97.17 - 0.425 97.59 0.05 4.86 4.91 102.5 4.88 107.38 50.47 52 13d 114 37.51 158.06 - 0.392 158.45 0.08 7.9 7.98 166.43 7.92 174.35 81.95 53 14a 136 31.22 142 - 4.32 146.32 0.15 7.1 7.25 153.57 7.32 160.89 75.62 54 14b 84 15.07 59.25 - 4.3 63.55 0.24 2.96 3.2 66.75 3.18 69.93 32.87 55 14c 118 32.76 114.59 - 3.62 118.21 0.1 5.73 5.83 124.04 5.91 129.95 61.08 S.

AGB Herbaceous

56 14d 93 21.14 76.09 - 5.2 81.29 0.15 3.8 3.95 85.24 4.06 89.3 41.97 57 15a 94 26.52 107.31 1.5 2.416 111.21 0.47 5.37 5.84 117.05 5.56 122.61 57.63 58 15b 87 23.81 96.35 0.76 2.01 99.12 0.38 4.82 5.2 104.32 4.96 109.28 51.36 59 15c 92 26.71 109.18 0.85 2.128 112.14 0.67 5.46 6.13 118.27 5.61 123.88 58.22 60 15d 95 21.92 108.16 0.6 2.044 110.8 0.43 5.41 5.84 116.64 5.54 122.18 57.42 61 16a 68 12.08 34.7 0.12 0.921 35.74 1.08 1.74 2.82 38.56 1.79 40.35 18.96 62 16b 81 15.81 45.4 0.28 1.244 46.92 0.86 2.27 3.13 50.05 2.35 52.4 24.63 63 16c 95 16 44.77 0.15 1.358 46.26 0.92 2.24 3.16 49.42 2.31 51.73 24.31

64 16d 87 14.51 41.47 0.17 1.058 43.68 1.01 2.07 3.08 46.76 2.18 48.94 23 65 17a 96 14.06 36.65 0.2 1.152 38 0.85 1.83 2.68 40.68 1.9 42.58 20.01 66 17b 98 21.12 78.26 0.29 1.457 79.99 1.06 3.91 4.97 84.96 4 88.96 41.81 67 17c 93 12.62 39.97 0.62 1.657 42.23 0.92 2 2.92 45.15 2.11 47.26 22.21 68 17d 96 24.63 143.65 0.45 1.4 145.49 0.64 7.18 7.82 153.31 7.27 160.58 75.47 69 18a 87 14.27 35.09 0.91 1.234 37.22 1.2 1.75 2.95 40.17 1.86 42.03 19.75 S.

No. Plot ID

Trees/Liana Shrub AGB

Herbaceous AGB

AGLB Litter Dead Wood AGDB TAGB BGB TB Carbon TNI BA AGB

70 18b 97 15.88 48.97 0.71 1.536 51.2 0.64 2.45 3.09 54.29 2.56 56.85 26.72 71 18c 92 7.88 27.3 0.59 1.554 29.44 0.82 1.37 2.19 31.63 1.47 33.1 15.56 72 18d 88 22.88 80.75 0.59 1.41 82.74 1.07 4.04 5.11 87.85 4.14 91.99 43.23 73 19a 104 19.21 52.69 2.14 1.156 55.97 1.34 2.63 3.97 59.94 2.8 62.74 29.49 74 19b 101 17.55 47.27 0.38 1.208 48.85 0.91 2.36 3.27 52.12 2.44 54.56 25.64 75 19c 93 18.23 51.7 0.35 1.35 53.4 0.87 2.59 3.46 56.86 2.67 59.53 27.98 76 19d 88 13.87 38.24 2.83 1.134 42.19 1.08 1.91 2.99 45.18 2.11 47.29 22.23 77 20a 97 15 50.17 1.16 1.738 53.05 1.19 2.51 3.7 56.75 2.65 59.4 27.92 78 20b 86 85.62 299.3 1.21 2.07 302.58 0.97 14.97 15.94 318.52 15.13 333.65 156.82 79 20c 101 21.95 98.63 2.24 1.914 102.78 0.85 4.93 5.78 108.56 5.14 113.7 53.44 80 20d 96 15.79 51.03 2.14 1.42 54.59 1.09 2.55 3.64 58.23 2.73 60.96 28.65 81 21a 139 12.59 42.47 - 1.2 43.67 0.25 2.12 2.37 46.04 2.18 48.22 22.67 82 21b 120 11.91 39.97 - 2.726 42.69 0.05 2 2.05 44.74 2.13 46.87 22.03 83 21c 173 10.06 33.88 - 2.182 36.06 0.04 1.69 1.73 37.79 1.8 39.59 18.61 S.

No. Plot ID

Herbaceous AGB

84 21d 167 6.04 20.63 - 1.2 21.83 0.15 1.03 1.18 23.01 1.09 24.1 11.33 85 22a 99 8.35 29.1 - 3.423 32.52 0.36 1.46 1.82 34.34 1.63 35.97 16.9 86 22b 113 7.56 29.01 0.19 1.86 31.06 0.05 1.45 1.5 32.56 1.55 34.11 16.03 87 22c 114 7.04 26.2 - 1.978 28.17 0.08 1.31 1.39 29.56 1.41 30.97 14.56 88 22d 133 9.31 33.16 - 2.567 35.72 0.2 1.66 1.86 37.58 1.79 39.37 18.5 89 23a 125 36.09 125.14 - 2.723 127.86 0.11 6.26 6.37 134.23 6.39 140.62 66.09 90 23b 123 14.4 53.16 - 3.11 56.27 0.24 2.66 2.9 59.17 2.81 61.98 29.13 91 23c 123 26.33 81.23 0.02 2.992 84.23 0.05 4.06 4.11 88.34 4.21 92.55 43.5 92 23d 129 23.92 89.09 - 2.315 91.4 0.15 4.45 4.6 96 4.57 100.57 47.27 93 24a 98 19.15 74.56 0.23 2.914 77.69 0.06 3.73 3.79 81.48 3.88 85.36 40.12 94 24b 92 21.83 95.43 0.56 1.991 97.97 0.92 4.77 5.69 103.66 4.9 108.56 51.02 95 24c 97 14.52 60.64 0.24 2.731 63.6 1.08 3.03 4.11 67.71 3.18 70.89 33.32 96 24d 89 11.38 37.66 0.2 2.392 40.25 0.72 1.88 2.6 42.85 2.01 44.86 21.09 97 25a 87 17.78 73.76 1.09 1.052 75.8 0.64 3.68 4.32 80.12 3.79 83.91 39.44 S.

No. Plot ID

Herbaceous AGB

98 25b 91 19.44 75.92 1.55 1.19 78.66 1.28 3.8 5.08 83.74 3.93 87.67 41.21 99 25c 84 17.35 67.56 1.01 1.142 69.7 1.05 3.38 4.43 74.13 3.49 77.62 36.48 100 25d 92 13.01 104 0.65 1.222 105.86 0.83 5.2 6.03 111.89 5.29 117.18 55.08 101 26a 100 27.91 118.52 0.48 2.807 121.8 0.71 5.93 6.64 128.44 6.09 134.53 63.23 102 26b 88 17.57 64.07 0.23 2.866 67.16 0.82 3.2 4.02 71.18 3.36 74.54 35.03 103 26c 92 19 57.32 0.4 3.396 61.11 1.05 2.87 3.92 65.03 3.06 68.09 32 104 26d 117 24.87 79.56 0.43 2.82 82.8 0.46 3.98 4.44 87.24 4.14 91.38 42.95 105 27a 116 27.76 86.92 1.04 2.492 90.45 0.33 4.35 4.68 95.13 4.52 99.65 46.84 106 27b 95 23.21 72.94 0.01 4.226 77.17 0.24 3.65 3.89 81.06 3.86 84.92 39.91 107 27c 103 45.5 153.51 - 3.109 156.61 0.28 7.68 7.96 164.57 7.83 172.4 81.03 108 27d 104 22.92 85.55 1.42 3.385 90.34 0.1 4.28 4.38 94.72 4.52 99.24 46.64 109 28a 102 14.77 92.76 0.31 2.745 95.8 0.84 4.64 5.48 101.28 4.79 106.07 49.85 110 28b 119 15.11 100.08 0.4 2.744 103.22 0.92 5 5.92 109.14 5.16 114.3 53.72 111 28c 97 19.35 58.67 0.5 2.514 61.68 0.46 2.93 3.39 65.07 3.08 68.15 32.03 S.

No. Plot ID

Herbaceous AGB

112 28d 86 18.01 111.39 0.21 2.455 114.05 0.85 5.57 6.42 120.47 5.7 126.17 59.3 113 29a 117 24.93 77.74 - 3.41 81.15 0.41 3.89 4.3 85.45 4.06 89.51 42.07 114 29b 135 31.07 117.35 - 1.67 119.02 0.31 5.87 6.18 125.2 5.95 131.15 61.64 115 29c 139 40.16 148.79 - 1.76 150.55 0 7.44 7.44 157.99 7.53 165.52 77.79 116 29d 104 21.92 71.49 - 2.19 73.68 0.1 3.57 3.67 77.35 3.68 81.03 38.09 117 30a 189 10.5 26.4 - 2.23 28.63 0.02 1.32 1.34 29.97 1.43 31.4 14.76 118 30b 146 7.62 23.93 - 3.15 27.08 0.08 1.2 1.28 28.36 1.35 29.71 13.97 119 30c 178 10.98 37.81 - 2.765 40.57 0.14 1.89 2.03 42.6 2.03 44.63 20.98 120 30d 187 11.54 42.34 - 2.486 44.82 0 2.12 2.12 46.94 2.24 49.18 23.12

Mean - 17.47 64.19 0.76 1.85 66.36 0.44 3.2 3.65 70.024 3.31 73.34 34.47 ±SD - ±10.99 ±42.63 ±0.64 ±1.11 ±42.87 ±0.36 ±2.13 ±2.21 ±45.05 ±2.14 ±47.20 ±22.18

ABBREVIATIONS: TNI-Total Number of Individuals, BA-Basal Area, AGB-Above-Ground Biomass, AGLB-Above Ground Live Biomass, AGDB-Above Ground Dead Biomass, TAGB-Total Above-Ground Biomass, BGB-Below Ground Biomass, TB-Total Biomass, SD-Standard

Deviation

Fig. 1: Location map of the study area (Source: Google Earth) and sampled sites located with ARC-VIEW GIS (3.2 Version)

Carbon Stocks The total carbon stock density of the sampled inventory is 34.48±22.18 Mg C ha-1 and ranges 3.22-156.84 Mg C ha-1

across the plots (Table 1). Carbon densities in different components of the study area are as follows: trees/liana 30.17 Mg C ha-1, shrubs 0.35 Mg C ha-1, herbaceous 0.87 Mg C ha-1, above-ground live 31.19 Mg C ha-1, litter 0.20 Mg C ha-1, dead wood 1.51 Mg C ha-1, above-ground dead 1.71 Mg C ha-1, total above-ground 32.91 Mg C ha-1 and below ground 1.55 Mg C ha-1. The percentage values shared by these components are represented in Fig. 3. The total carbon pool is extrapolated as 26.34 Mt for Nalllamalais.

The carbon density of 34 Mg C ha-1 was reported for Indian forests [27] and this is similar to the estimates of the present study. However, it is found lower than the estimates of dry deciduous forests (64.35 Mg ha-1); mixed deciduous forests (129.0 Mg ha-1) of East Godavari district of Andhra Pradesh [43] and tropical deciduous forests of India (99.44 Mg ha-1 ) [44].

y = 3.6808x + 0.264

R2 = 0.8704

0 10 20 30 40 50 60 70

Basal Area m2 ha-1

Fig. 2: Correlation between basal area and biomass of trees ≥10 cm diameter

Fig. 3: Percentages shared by different components of Carbon stocks

0.6 2.53

T rees BGB Dead Wood Herbs Litter Shrubs

The total carbon stock in Indian forests worked out in different studies and respective share of carbon stock of Nallamalais estimated in our study are: 9585 Mt by Ravindranath et al., [6] (Nallamalais, 0.27%); 2940 Tg by Haripriya [45] (0.89%); 10.01 Gt by FAO [46] (0.26%); 2865.739 Mt by Kishwan et al., [39] (0.9%) and 6622 Mt by FSI [26] (0.39%). Nallamalais by having an estimated carbon stocks of 26.34 Mt had the sequestration potential of 97.568 Mt of atmospheric carbon dioxide based on Frederick M. O’Hara [47].

CONCLUSION

The present study pertaining to estimation of carbon sequestration potential of tropical deciduous forests of Nallamalais in Eastern Ghats of Andhra Pradesh covered 120 sampled plots of size 0.1ha and recorded a total of 306 plant species. The total aboveground biomass (TAGB) estimated for Nallamalais is 53.49 Mt of which AGLB is 50.69 Mt and AGDB is 2.78 Mt. Of the AGLB, trees/liana comprises 49.041 Mt (97.3%), shrubs contribute 0.58 Mt (0.47%) and herbaceous 1.41 Mt (2.79%). Of the AGDB, litter contributes 0.33 Mt (12.97%) and dead wood 2.44 Mt (87.81%). BGB of Nallamalais is estimated at 2.551 Mt and accounts for 4.52% of the total biomass. Thus, the total biomass density of Nallamalais is 73.36±47.20 Mg ha-1 and accounts for 56.047 Mt. The total carbon pool density of the study area is 34.48±22.18 Mg ha-1 and the total carbon stocks of the study area are estimated at 26.34 Mt which equals 97.568 Mt of sequestered atmospheric carbon dioxide. When compared with the total carbon stock in Indian forests worked out in different studies Nallamalais share 0.26% to 0.9% of the total national carbon stocks. It is observed that anthropogenic fire and illegal cutting of trees for timber has major impact on the carbon stocks of the forests of Nallamalais. Acknowledgements We are thankful to Indian Institute of Remote Sensing (IIRS), Dehra Dun (ISRO, Department of Space) for financial support and grateful to Dr. V.K. Dadhwal, Director; Dr. Sarnam Singh, Deputy Director; VCP Project for guidance and cooperation. Thanks are also due to the Andhra Pradesh Forest Department for help in field work.

REFERENCES

[1] Phillips OL, Gentry AH, Science, 1994, 263, 954. [2] Dixon RK, Brown S, Houghton RA, Solomon AM, Trexler MC, Wisniewski J, Science, 1994, 263, 185. [3] Ketterings QM, Coe R, van Noordwijk M, Ambagau Y, Palm CA, For Ecol Manage, 2001, 146, 199. [4] Chave J, Condit R, Aguilar S, Hernandez A, Lao S, Perez R, Phil Trans R Soc Lond, 2004, B 359, 409. (DOI 10, 1098/rstb.2003.1425). [5] Dadhwal VK, Nayak SR, Science and Culture, 1993, 59, 9. [6] Ravindranath NH, Somashekar BS, Gadgil M, Climatic Change, 1997, 35, 297. [7] Chhabra A, Dadhwal VK, Climatic Change, 2004, 64, 341. [8] Davis SD, Heywood VH, Hamilton AC, Centers of Plant Diversity: A Guide and Strategy for Their Conservation. Volume 2: Asia, Australia and the Pacific, WWF and IUCN, Cambridge, UK, 1995. [9] Champion HG, Seth SK, Forest Types of India, Government of India Press, Nassik, India. 1968. [10] Singh S, Dadhwal VK, Vegetation Carbon Pool Assessment in India (Field Manual). Department of Space, Government of India, Dehra Dun, India. 2008. [11] Dadhwal VK, Singh S, Patil P, NNRMS Bulletin, 2009, 41. [12] Patil P, Singh S, Dadhwal VK, In J Indian Soc Rem Sens, 2011. (DOI: 10.1007/s12524-011-0121-3). [13] Murali KS, Bhat DM. Ravindranath NH, In J Agri Res Gov Ecol, 2004, 10(10), 1. [14] Annon, Volume Equations for Forests of India, Nepal and Bhutan. Forest Survey of India, Ministry of Environment and Forests, Dehra Dun, India. 1996. [15] Reyes G, Brown S, Chapman J, Lugo AE, Wood densities of tropical tree species. U.S. Department of Agriculture, Forest Service, New Orleans, LA. 1992. [16] Annon, Indian Woods. Volume I-VI. Forest Research Institute, Ministry of Environment and Forests, Dehra Dun, India. 1996. [17] Mani S, Parthasarathy N, Biomass and Bioenergy, 2007, 31, 284. [18] Brown S, Gillespie AJR, Lugo AE, For Sci, 1989, 35(4), 881. [19] Rajput SS, Sulkha NK, Gupta VK, Jain JD, Indian Council of Forestry Research and Education, Dehra Dun, India. ICFRE Publication-38, 1996, p. 103. [20] Achard F, Eva HD, Stibig H-J, Mayaux P, Gallego J, Richards T, Malingrean J-P, Science. 2002, 297, 999. [21] Ramankutty N, Gibbs HK, Achard F, DeFries R, Foley JA, Houghton RA, Glob Chan Biol, 2007, 13, 51.

[22] McGroddy ME, Daufresne T, Hedin LO, Ecology, 2004, 85, 2390. [23] Guo Z, Fang J, Pan Y, Bridsey R, For Ecol Manage, 2010. 259, 1225,. [24] Mani S, Parthasarathy N, Trop Ecol, 2009, 50(2), 249. [25] Ramachandran A, Jayakumar S, Haroon RM, Bhaskaran A, Arockiasamy DI, Curr Sci, 2007, 92(3), 323,. [26] Annon, India State of Forest Report 2009. Forest Survey of India, Ministry of Environment and Forests, Government of India, Dehradun, India. 2009. [27] Haripriya GS, Biomass and Bioenergy, 2000, 19, 245. [28] Cannell MGR, For Ecol Manage, 1984, 8, 299. [29] Clark DA, Brown S, Kicklighter D, Chambers JQ, Thomlinson JR, Ni J, Ecological Applications, 2001, 11, 356. [30] Pande PK, Trop Ecol, 2005. 46(2), 229. [31] Roy PS, Ravan SA, Journal of Bioscience, 1996, 21(4), 535. [32] Singh V, Tewari A, Kushwaha SPS, Dadhwal VK, For Ecol Manage, 2011, 261, 1945. [33] Swamy SL, Dutt CBS, Murthy MSR, Mishra A, Bargali SS, Curr Sci, 2010, 99(3), 353. [34] Harmon ME, Brown S, Gower ST, In: Vinson TS, Kolchugina TP (Ed.), Symposium on Consequences of tree mortality to the Global carbon cycle; Carbon Cycling in Boreal and Subarctic Ecosystems; Biospheric Response and Feedbacks to Global Climate Change. USEPA, Corvallis, OR, 1993. pp. 167. [35] Siitonen J, Ecological Bulletin, 2001, 49, 11. [36] Naesset E, Can J For Res, 1999, 14, 454. [37] FAO, Forestry Paper 163, Rome, Italy. 2010. (www.fao.org/forestry/fra/fra2010/en/). [38] Schlegel BC, Donoso PJ, For Ecol Manage, 2008, 255, 1906. [39] Kishwan J, Pandey R, Dadhwal VK, Indian Council of Forestry Research and Education, Dehra Dun, India. Technical Paper No 130 ICFRE BI-23. 2009. [40] Madugundu R, Nizalapur V, Jha CS, In J Applied Earth Observations, 2008, (Doi: 10, 1016/j.jag.2007.11.004). [41] Cannell MGR; World forest biomass and primary production data. Academic, London, 1982. [42] Sicard C, Saint-Andre L, Gelhaye D, Ranger J, Struct Funct, 2006, 20, 229. [43] Prasad VK, Kant Y, Badarinath KVS, Geocarto International, 2000, 15(2), 71. [44] Singh L, Yadav DK, Pagare P, Gosh L, Thakur BS, In J Ecol Environ Sci, 2009, 35(1), 113. [45] Haripriya GS, For Ecol Manage, 2002, 168, 1. [46] FAO, Roem. Italy. 2005, p.147. (www.fao.org/forestry/fra/fra2005/en/). [47] O'Hara Jr FM, In: O'Hara Jr FM, (Ed.), Carbon Dioxide and Climate, 3rd Edn., (ORNL/CD IAC-39). Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee. 1990. (www.cdiac.ornl.gov/pns/convert.html).

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